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mirt (version 1.7)

Multidimensional Item Response Theory

Description

Analysis of dichotomous and polytomous response data using unidimensional and multidimensional latent trait models under the Item Response Theory paradigm. Exploratory and confirmatory models can be estimated with quadrature (EM) or stochastic (MHRM) methods. Confirmatory bi-factor and two-tier analyses are available for modeling item testlets. Multiple group analysis and mixed effects designs also are available for detecting differential item functioning and modelling item and person covariates.

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Install

install.packages('mirt')

Monthly Downloads

7,656

Version

1.7

License

GPL (>= 3)

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Maintainer

Phil Chalmers

Last Published

December 15th, 2014

Functions in mirt (1.7)

Science

Description of Science data
expected.item

Function to calculate expected value of item
DIF

Differential item functioning tests
key2binary

Convert response patterns to binary data
mixedmirt

Mixed effects modeling for MIRT models
PLCI.mirt

Compute profiled-likelihood confidence intervals
createItem

Create a user defined item with correct generic functions
testinfo

Function to calculate test information
mod2values

Convert an estimated mirt model to special data.frame
MixedClass-class

Class "MixedClass"
M2

Compute M2 statistic
averageMI

Collapse values from multiple imputation draws
DTF

Differential test functioning
mirt-package

Full information maximum likelihood estimation of IRT models.
extract.group

Extract a group from a multiple group mirt object
personfit

Person fit statistics
Bock1997

Description of Bock 1997 data
imputeMissing

Imputing plausible data for missing values
DiscreteClass-class

Class "DiscreteClass"
itemplot

Displays item surface and information plots
wald

Wald test for mirt models
mirt

Full-Information Item Factor Analysis (Multidimensional Item Response Theory)
extract.item

Extract an item object from mirt objects
boot.mirt

Calculate bootstrapped standard errors for estimated models
deAyala

Description of deAyala data
mirt.model

Specify model loadings
plot-method

Plot various test implied functions from models
bfactor

Full-Information Item Bi-factor and Two-Tier Analysis
fscores

Methods for Function fscores
simdata

Simulate response patterns
print-method

Print the model objects
SingleGroupClass-class

Class "SingleGroupClass"
residuals-method

Compute model residuals
LSAT6

Description of LSAT6 data
MultipleGroupClass-class

Class "MultipleGroupClass"
LSAT7

Description of LSAT7 data
SAT12

Description of SAT12 data
expected.test

Function to calculate expected test score
mdirt

Multidimensional discrete item response theory
probtrace

Function to calculate probability trace lines
expand.table

Expand summary table of patterns and frequencies
summary-method

Summary of model object
anova-method

Compare nested models
iteminfo

Function to calculate item information
multipleGroup

Multiple Group Estimation
randef

Compute random effects
mirtCluster

Define a parallel cluster object to be used in internal functions
coef-method

Extract raw coefs from model object
itemfit

Item fit statistics
show-method

Show model object